Current worldwide environmental concerns have fueled an increase in efforts to recycle used equipment and articles containing materials that can be reused. Such efforts have produced new and improved processes for sorting materials such as plastics, glasses, metals, and metal alloys.
As used herein, a “material” may be a chemical element, a compound or mixture of two or more chemical elements, or a compound or mixture of a compound or mixture of chemical elements, or any suitable combination thereof, wherein the complexity of a compound or mixture may range from simple to complex. Types of materials include organic materials, metals (ferrous and non-ferrous), metal alloys, plastics, polymers, rubber, glasses, ceramics, fabrics, other materials and any suitable combination thereof. As used herein, “element” means a chemical element of the periodic table of elements, including elements that may be discovered after the filing date of this application.
Generally, methods for sorting pieces of materials involve determining one or more properties, for example, one or more physical and/or chemical properties, of each piece, and grouping together pieces sharing a common property or properties. Such properties may include color, hue, texture, weight, density, transmissivity to light, sound, or other signals, and reaction to stimuli such as various fields. Methods to determine these properties include visual identification of a material by a person, identification by the amount and/or wavelength of the light waves emitted or transmitted (commonly referred to as optical emission spectroscopy or OES), eddy-current separation, heavy-media plant separation, and x-ray fluorescence (XRF) detection.
With respect to metals and metal alloys, today it is neither technically nor commercially feasible to separate and recover many of the non-ferrous metals that are manufactured into products and discarded at the end of their useful life. In residential waste, only aluminum cans are recycled to any significant degree. Virtually none of the other non-ferrous materials in our residential waste are recovered. Instead, they are disposed in landfills. Further, in the U.S., small non-ferrous materials below ⅝ inches (˜1.5 cm) in size are landfilled from nearly 200 automobile shredders.
Smaller-sized pieces of non-ferrous metals from automobile shredders are not separated because their recovery is not cost-effective. They can only be consolidated and shipped to larger facilities for further processing. Mixed non-ferrous metals from industrial processes are often disposed or junked because hand-sorting and small-particle recovery technologies either do not work well or are not cost-effective. Nearly 2 billion pounds of valuable non-ferrous metals are discarded in landfills every year in the U.S. alone. Worldwide, the amount of metal wasted is far greater. If this metal could be economically recycled at high volumes, the potential value generated is estimated to be in excess of 1 billion dollars (U.S.) per year. Further, there are approximately 200 waste-to-energy facilities, 200 automobile shredders, and thousands of metal scrap yards in the U.S. alone that could benefit financially (and otherwise) from an improved sorting system.
OES, mentioned above, is a known technique for sorting scrap metal, for example, as described in U.S. Pat. No. 6,545,240 B2, titled “Metal Scrap Sorting System” by Kumar, the entire contents of which are hereby incorporated by reference. A known problem with OES systems is that OES is not efficient at identifying a wide-range of metals and, therefore, typically is calibrated for use on a particular alloy group. For example, an OES system may be used to identify aluminum alloys only or magnesium alloys only. Applicant's understanding of the source of this problem is as follows. In order to achieve accurate identification for different base metals of alloys, known OES systems require that the calibration settings for OES spectral identification be adjusted for each group. For example, the calibration setting for an aluminum alloy is different than the calibration settings for a nickel alloy. As used herein, a “base metal” of an alloy is the metal having the largest percentage of the mass of the constituent elements of the alloy.
In contrast, XRF spectroscopy is well-suited for classifying a wide-range of metals, including the base metals of alloys. XRF spectroscopy has long been a useful analytical tool in the laboratory for classifying materials by identifying elements within the material, both in academic environments and in industry. The use of characteristic x-rays such as, for example, K-shell or L-shell x-rays, fluoresced from elements in response to being stimulated by x-rays, provides a method for positive identification of elements and their relative amounts present in different materials, such as metals and metal alloys. For example, radiation striking matter causes the emission of characteristic K-shell x-rays when a K-shell electron is knocked out of the K-shell by incoming radiation and is then replaced by an outer shell electron. The outer electron, in dropping to the K-shell energy state, emits x-ray radiation characteristic of the atom.
The energy of emitted x-rays depends on the atomic number of the fluorescing elements. Energy-resolving detectors can detect the different energy levels at which x-rays are fluoresced, and generate an x-ray signal from the detected x-rays. This x-ray signal then may be used to build an energy spectrum of the detected x-rays, and from the information, the element or elements which produced the x-rays may be identified. X-rays are fluoresced from an irradiated element and the detected radiation depends on the solid angle subtended by the detector and any absorption of this radiation prior to the radiation reaching the detector. The lower the energy of an x-ray, the shorter the distance it travels before being absorbed by air. Thus, when detecting x-rays, the amount of x-rays detected is a function of the intensity of x-rays emitted, the energy level of the emitted x-rays, the emitted x-rays absorbed in the transmission medium, the angles between the fluoresced x-rays and the detector, and the distance between the detector and the irradiated material.
Although x-ray spectroscopy is a useful analytical tool for classifying materials, with current technology, the cost is high per analysis, and the time required is typically several seconds to minutes or hours. For example, some hand-held x-ray analyzers are able to acquire an XRF spectrum from a piece of scrap metal in approximately five to fifteen seconds, after which the user sorts the piece of scrap metal by hand. There are bench-top XRF systems that are capable of acquisition times within this range as well. Because of these relatively long analysis times, scrap yard identification of metals and alloys is primarily accomplished today by trained sorters who visually examine each metal object one at a time. Contamination is removed by shearing. A trained sorter observes subtle characteristics of color, hue, texture, and density to qualitatively assess the composition of the metal. Sometimes, spark testing or chemical “litmus” testing aids in identification. The process is slow and inaccurate, but is the most common method in existence today for sorting scrap metal to upgrade its value.
There have been disclosed a variety of systems and techniques for classifying materials based on the XRF of the material. Some of these systems involve hand-held or bench-top XRF detectors. These types of systems are less accurate than laboratory analyzers, but often give an accurate classification of the alloy in several seconds. Other systems include serially conveying pieces of material along a conveyor belt and irradiating each piece, in turn, with x-rays. These x-rays cause each piece of material to fluoresce x-rays at various energy levels, depending on the elements contained in the piece. The fluoresced x-rays are detected, and the piece of material is then classified based on the fluoresced x-rays, and is automatically sorted in accordance with this classification.
Such disclosed systems, however, have not been widely accepted commercially because they require more than one second to detect the x-rays and accurately classify the piece of material accordingly, and they are expensive relative to the number of objects identified per unit time.
An improved approach to sorting scrap metal and other materials is disclosed in U.S. Pat. No. 6,266,390, titled “High Speed Materials Sorting System Using XRF” by Sommer, Jr. et al. (hereinafter, “the Sommer patent”), the entire contents of which are hereby incorporated by reference. In the Sommer patent, XRF sensing is applied to classify pieces of material as small as ¼ inches, which are conveyed in a singulated stream through a sensing region at speeds as fast as 60 in/sec. to 120 in/sec. The Sommer patent discloses a novel system that employs fast-sorting techniques, algorithms and equipment to irradiate the pieces causing them to fluoresce x-rays, detect the x-rays, classify the piece based on the detected x-rays and sort the pieces off of the fast-moving conveyor belt at speeds as fast as 10 pieces per second or more.
A problem with known sorting systems, whether hand-held, bench-top, or a system involving conveyor belts, is the difficulty of using XRF spectroscopy to accurately classify pieces of material containing elements with low atomic number (i.e., low-Z elements). As used herein, a “low-Z element” is an element in the periodic table of elements having an atomic number of less than 22, i.e., less than the atomic number of titanium. As used herein, a “high-Z element” is an element in the periodic table of elements (including elements added after the filing date of this application) having an atomic number of 22 or greater, i.e., the atomic number of titanium or greater. For example, detection of pieces containing aluminum, which has an atomic number of 13, and other low-Z elements such as silicon and magnesium, is difficult with XRF spectroscopy. The problem is two-fold. First, the x-rays (even the x-rays of highest energy—K-alpha x-rays) fluoresced from the low-Z elements are at very low energy (e.g., approximately between 1-2 keV) such that they are easily absorbed in air. Second, for a given amount of x-rays (i.e., the x-rays from an x-ray source) irradiating a piece, low-Z elements within the piece fluoresce less x-rays than high-Z elements within the piece. The low-Z elements fluoresce less x-rays because the low-Z elements have a sparser concentration of electrons than the high-Z elements. Thus, for a given amount of impacting x-rays, there is a lower probability of dislodging electrons shells (i.e., energy levels) of low-Z elements than from shells of high-Z elements.
FIG. 1 is a graph 100 illustrating values of the x-ray energy for various common metals encountered in recycling. The energies for three different types of x-rays, Kα, Lα, and Lβ, are shown in FIG. 3 (shown as Ka, La and Lb, respectively). K x-rays are x-rays resulting from an electron of a K-shell of an atom (the inner most shell) being expelled or knocked out of the k-shell and being replaced by an electron from an outer shell (e.g., L-Q). A Kα x-ray is an x-ray resulting from when the replacing electron is from the next closest outer shell, L, whereas a Kβ x-ray (not shown) is an x-ray resulting from when the replacing electron is from the M-shell. L x-rays are x-rays resulting from an electron of an L-shell of an atom (the next inner most shell) being expelled or knocked out of the L-shell and being replaced by an electron from an outer shell (e.g., M-Q). An Lα x-ray is an x-ray resulting from when the replacing electron is from the next closest outer shell, M, whereas a Kβ x-ray is an x-ray resulting from when the replacing electron is from the N-shell. K x-rays have a higher energy than L x-rays.
From FIG. 1, it can be seen that the energy and yield of fluoresced x-rays is small for aluminum and magnesium compared to the other metals. FIG. 1 also illustrates the percentage of x-rays, for different energy levels, transmitted through air over various distances without first being absorbed by air (these calculations were determined by approximating the density of air to being equal to that of nitrogen). Curve 102 represents the percentage of x-rays transmitted a distance of 12.7 mm. Curve 104 represents the percentage of x-rays transmitted a distance of 25.4 mm, and curve 106 represents the percentage of x-rays transmitted a distance of 38.1 mm. As is illustrated by curves 102, 104, 106, the percentage of x-rays transmitted without being absorbed by air increases as the energy of the x-rays increases and as the distance decreases.
One solution to the above problem, at least for sorting pieces of material containing only low-Z elements, is sorting pieces of material by “difference”, i.e., by configuring a sorting system such that pieces of material containing only low-Z elements are the only pieces that are left on the conveyor belt after all other pieces have been classified and sorted. For example, the pieces containing only low-Z elements are sorted into a default bin. An example of this technique is described in the Sommer patent. This solution has some drawbacks. One drawback is that multiple low-Z elements cannot be sorted separately using this technique, as all pieces of material containing only low-Z elements are left on the conveyor belt.
Another drawback to this technique is that pieces of material containing both low-Z elements and high-Z elements may be incorrectly classified and sorted because at high speeds x-rays fluoresced by the high-Z elements may be the only fluoresced x-rays that are detected. Consider the case of aluminum. Aluminum alloys may have zinc and/or copper as an alloying agent, and some bronze alloys may have copper as the primary metal with aluminum as an alloying agent. Because an XRF sensor may be unable to detect x-rays fluoresced by aluminum when an aluminum alloy is exposed to x-rays for only a short time (e.g., in a high speed sorting system), these alloys may be mistakenly identified as zinc, copper, or brass (a copper alloy) and, consequently, may be mis-sorted, thereby contaminating the sorted zinc and copper pieces with pieces of aluminum alloy containing zinc and copper.
A hand-held LIBS analyzer for identifying pieces of scrap metal that contain one or more low-Z elements such as aluminum, magnesium and silicon has been disclosed. However, such an analyzer would be slow and cumbersome, requiring the operator to touch a piece of scrap metal, hold the analyzer in position for several seconds, read the output of the analyzer, and then manually sort the piece of material by moving it into a sorting bin or other suitable location. Further, such a hand-held analyzer would be useful only for identifying that pieces of materials contain low-Z elements, but not for classifying a broad range of materials, which may contain high-Z and low-Z elements in any of a variety of combinations.